Genetic variations in introns commonly impact cellular functions by causing alterations in mRNA splicing. The abnormal inclusion and exclusion of exons often change protein functions and cellular phenotypes. Although many intronic variations have known functions, with the adoption of next generation sequencing, many more intronic variants have been discovered for which the functional impact is unknown. Thus, it is important to be able to predict the impact of the variants without needing to test them all in expensive and laborious assays. Although there are informatics algorithms that predict the impact of genetic variants on pre-mRNA splicing, their ability to predict the effect on protein function and ultimately disease and therapeutic phenotypes is lacking. In addition, there is a need for high-throughput cellular assays to test the results of these predictions on cellular functions. The studies proposed here will fulfill these needs by developing algorithms that prioritize the intronic variants by their potential impact on splicing and gene function, and developing a high-throughput assay to functionally test thousands of these predictions. These novel technologies will be applied to the effect of intronic variants on the pharmacogenomics of two clinically important oncology drugs, clofarabine and paclitaxel. Our long-term goals are to be able to predict the functional impact of genomic variants on human disease and therapeutic response. Our central hypothesis is that intronic genetic variants alter mRNA splicing and consequently protein function that ultimately affects the cellular response to drug therapy. Our first aim will be to develop computational algorithms that prioritize intronic variants based on their impacts on pre-mRNA splicing and protein function. Using a variety of genomic and structural features and large sets of genomic data, we will develop a bioinformatics algorithm specifically designed to prioritize intronic variants based on their potential impacts on pre-mRNA splicing and protein function. Our second aim will be to identify functional intronic variants associated with drug-induced cytotoxicity. Using existing genomics and cellular cytotoxic response data from populations of human cell lines, we will identify functional intronic variants that contribute to individuals' responses to clofarabine and paclitaxel cytotoxicity. Our third aim will be to functionally test the impact of the prioritized intronic variants on pre-mRNA splicing and drug cytotoxicity. Using our novel high- throughput functional splicing assay, we will test the effects of predicted functional variants from Aim 2 on pre- mRNA splicing. In addition, we will validate the effect of the intronic variants on cytotoxicity using exon specific siRNA and CRISPR/Cas technology to manipulate the target gene splicing. Upon completion of these studies, we expect to have developed bioinformatics algorithms that can accurately prioritize the intronic variants based on their functional impact on pre-mRNA splicing and protein function. Also, we will have tested thousands of variants in a cellular pre-mRNA splicing assay and validated the impact of several of these functional variants on paclitaxel and clofarabine cytotoxicity.